Owing to the constraints of depth sensing technology,images acquired by depth cameras are inevitably mixed with various noises.For depth maps presented in gray values,this research proposes a novel denoising model,ter...Owing to the constraints of depth sensing technology,images acquired by depth cameras are inevitably mixed with various noises.For depth maps presented in gray values,this research proposes a novel denoising model,termed graph-based transform(GBT)and dual graph Laplacian regularization(DGLR)(DGLR-GBT).This model specifically aims to remove Gaussian white noise by capitalizing on the nonlocal self-similarity(NSS)and the piecewise smoothness properties intrinsic to depth maps.Within the group sparse coding(GSC)framework,a combination of GBT and DGLR is implemented.Firstly,within each group,the graph is constructed by using estimates of the true values of the averaged blocks instead of the observations.Secondly,the graph Laplacian regular terms are constructed based on rows and columns of similar block groups,respectively.Lastly,the solution is obtained effectively by combining the alternating direction multiplication method(ADMM)with the weighted thresholding method within the domain of GBT.展开更多
A significant advantage of medical image processing is that it allows non-invasive exploration of internal anatomy in great detail.It is possible to create and study 3D models of anatomical structures to improve treatm...A significant advantage of medical image processing is that it allows non-invasive exploration of internal anatomy in great detail.It is possible to create and study 3D models of anatomical structures to improve treatment outcomes,develop more effective medical devices,or arrive at a more accurate diagnosis.This paper aims to present a fused evolutionary algorithm that takes advantage of both whale optimization and bacterial foraging optimization to optimize feature extraction.The classification process was conducted with the aid of a convolu-tional neural network(CNN)with dual graphs.Evaluation of the performance of the fused model is carried out with various methods.In the initial input Com-puter Tomography(CT)image,150 images are pre-processed and segmented to identify cancerous and non-cancerous nodules.The geometrical,statistical,struc-tural,and texture features are extracted from the preprocessed segmented image using various methods such as Gray-level co-occurrence matrix(GLCM),Histo-gram-oriented gradient features(HOG),and Gray-level dependence matrix(GLDM).To select the optimal features,a novel fusion approach known as Whale-Bacterial Foraging Optimization is proposed.For the classification of lung cancer,dual graph convolutional neural networks have been employed.A com-parison of classification algorithms and optimization algorithms has been con-ducted.According to the evaluated results,the proposed fused algorithm is successful with an accuracy of 98.72%in predicting lung tumors,and it outper-forms other conventional approaches.展开更多
Kinetic facades possess aesthetic expressiveness and environmental responsiveness,aligning with the principles of low-carbon architecture.Current kinetic facades primarily rely on three-dimensional movement,which are ...Kinetic facades possess aesthetic expressiveness and environmental responsiveness,aligning with the principles of low-carbon architecture.Current kinetic facades primarily rely on three-dimensional movement,which are characterized by complex structures and distributed drives,resulting in monotonous form,low robustness,and high costs.This paper focuses on the design of two-dimensional kinetic facades,proposing a hinged tessellation generation method based on the duality principle.First,the paper discusses the value and principles of applying dual graphs in HT,and then proposes a method of generating HT by adding hinged plates.Then,the operation process for different tessellation types is elaborated upon.Finally,a conceptual design is proposed to illustrate the potential of this method on kinetic facades.The method proposed in this paper is applicable to all uniform tessellations and Voronoi tessellations,capable of generating an infinite variety of planar expandable structures with small spatial thickness,simple structures,stable movements.Additionally,these structures can be driven to expand by a single driving point,enabling continuous adjustment in response to the requirement.It has significant application value in fields such as architectural and decorative design,structural design,mechanical design,industrial product and graphic design.展开更多
A definition of a self-dual code on graph and a procedure based on factor graphs to judge a self-dual code were presented. Three contributions of this paper were described as follows. To begin with, transform T_ R→L ...A definition of a self-dual code on graph and a procedure based on factor graphs to judge a self-dual code were presented. Three contributions of this paper were described as follows. To begin with, transform T_ R→L were defined, which was the basis of self-dual codes defined on graphs and played a key role in the paper. The second were that a self-dual code could be defined on factor graph, which was much different from conventional algebraic method. The third was that a factor graph approach to judge a self-dual code was illustrated, which took advantage of duality properties of factor graphs and our proposed transform T_ R→L to offer a convenient and geometrically intuitive process to judge a self-dual code.展开更多
陆地碳汇是碳循环的重要组成部分,在全球气候变化背景下其重要性日益凸显,相关研究受到了国内外学术界的广泛关注。采用文献计量方法,以1994—2024年间Web of Science核心合集SCI-E数据库以及CNKI数据库中所收录的共计8431篇相关文献为...陆地碳汇是碳循环的重要组成部分,在全球气候变化背景下其重要性日益凸显,相关研究受到了国内外学术界的广泛关注。采用文献计量方法,以1994—2024年间Web of Science核心合集SCI-E数据库以及CNKI数据库中所收录的共计8431篇相关文献为研究对象,运用CiteSpace软件绘制国内外文献共被引、作者共作以及关键词时间线等可视化图谱,分析了论文时间、学科、期刊以及来源国家的分布情况,给出了高影响机构、高产作者以及重要研究文献,并基于Burst检测探究了不同阶段关键词演化发展过程及未来趋势。结果表明:①近30 a来陆地碳汇发文量显著增长,2008年以后年均增幅12%,2019年以后年均增幅高达15%。②发文量较多的国家依次是中国、美国、德国、英国、加拿大等;高影响的研究机构主要有中国科学院、中国科学院大学、法国国家科学研究中心、美国农业部、巴黎-萨克雷大学等。③关键词演化过程主要分为3个阶段:1994—2008年侧重于碳循环基础理论研究,关键热词是碳循环、碳平衡和涡度相关等;2008—2019年研究热点从地球生态系统逐渐扩展到社会经济等方面,关键热词是净初级生产量、碳交换、生态补偿和低碳经济等;2019年至今紧密围绕全球碳减排目标与生态系统价值实现,关键热词是以碳中和、碳排放、温度敏感性、生态产品核算和碳交易;未来发展方向是碳汇监测核算、减排增汇提升方法、碳交易市场机制、深化国际合作等。研究成果可为厘清全球陆地碳汇发展脉络和研究热点、预测未来发展方向,以及促进我国双碳目标实现提供基础资料和政策建议。展开更多
Graph theory has a significant impact and is crucial in the structure of many real-life situations.To simulate uncertainty and ambiguity,many extensions of graph theoretical notions were created.Planar graphs play a v...Graph theory has a significant impact and is crucial in the structure of many real-life situations.To simulate uncertainty and ambiguity,many extensions of graph theoretical notions were created.Planar graphs play a vital role in modelling which has the property of non-crossing edges.Although crossing edges benefit,they have some drawbacks,which paved the way for the introduction of planar graphs.The overall purpose of the study is to contribute to the conceptual development of the Pythagorean Neutrosophic graph.The basic methodology of our research is the incorporation of the analogous concepts of planar graphs in the Pythagorean Neutrosophic graphs.The significant finding of our research is the introduction of Pythagorean Neutrosophic Planar graphs,a conceptual blending of Pythagorean Neutro-sophic and Planar graphs.The idea of Pythagorean Neutrosophic multigraphs and dual graphs are also introduced to deal with the ambiguous situations.This paper investigates the Pythagorean Neutrosophic planar values,which form the edges of the Pythagorean neutrosophic graphs.The concept of Pythagorean Neutrosophic dual graphs,isomorphism,co-weak and weak isomorphism have also been explored for Pythagorean Neutrosophic planar graphs.A decision-making algorithm was proposed with a numerical illustra-tion by using the Pythagorean Neutrosophic fuzzy graph.展开更多
Fuzzy graph theory is used for solving real-world problems in different fields, in- cluding theoretical computer science, engineering, physics, combinatorics and medical sciences. In this paper, we present conepts of ...Fuzzy graph theory is used for solving real-world problems in different fields, in- cluding theoretical computer science, engineering, physics, combinatorics and medical sciences. In this paper, we present conepts of bipolar neutrosophic multigraphs, bipolar neutrosophic planar graphs, bipolar neutrosophic dual graphs, and study some of their related properties. We also describe applications of bipolar neutrosophic graphs in road network and electrical connections.展开更多
基金National Natural Science Foundation of China(No.62372100)。
文摘Owing to the constraints of depth sensing technology,images acquired by depth cameras are inevitably mixed with various noises.For depth maps presented in gray values,this research proposes a novel denoising model,termed graph-based transform(GBT)and dual graph Laplacian regularization(DGLR)(DGLR-GBT).This model specifically aims to remove Gaussian white noise by capitalizing on the nonlocal self-similarity(NSS)and the piecewise smoothness properties intrinsic to depth maps.Within the group sparse coding(GSC)framework,a combination of GBT and DGLR is implemented.Firstly,within each group,the graph is constructed by using estimates of the true values of the averaged blocks instead of the observations.Secondly,the graph Laplacian regular terms are constructed based on rows and columns of similar block groups,respectively.Lastly,the solution is obtained effectively by combining the alternating direction multiplication method(ADMM)with the weighted thresholding method within the domain of GBT.
文摘A significant advantage of medical image processing is that it allows non-invasive exploration of internal anatomy in great detail.It is possible to create and study 3D models of anatomical structures to improve treatment outcomes,develop more effective medical devices,or arrive at a more accurate diagnosis.This paper aims to present a fused evolutionary algorithm that takes advantage of both whale optimization and bacterial foraging optimization to optimize feature extraction.The classification process was conducted with the aid of a convolu-tional neural network(CNN)with dual graphs.Evaluation of the performance of the fused model is carried out with various methods.In the initial input Com-puter Tomography(CT)image,150 images are pre-processed and segmented to identify cancerous and non-cancerous nodules.The geometrical,statistical,struc-tural,and texture features are extracted from the preprocessed segmented image using various methods such as Gray-level co-occurrence matrix(GLCM),Histo-gram-oriented gradient features(HOG),and Gray-level dependence matrix(GLDM).To select the optimal features,a novel fusion approach known as Whale-Bacterial Foraging Optimization is proposed.For the classification of lung cancer,dual graph convolutional neural networks have been employed.A com-parison of classification algorithms and optimization algorithms has been con-ducted.According to the evaluated results,the proposed fused algorithm is successful with an accuracy of 98.72%in predicting lung tumors,and it outper-forms other conventional approaches.
基金supported by the National Natural Science Foundation of China(Grant No.52378043)。
文摘Kinetic facades possess aesthetic expressiveness and environmental responsiveness,aligning with the principles of low-carbon architecture.Current kinetic facades primarily rely on three-dimensional movement,which are characterized by complex structures and distributed drives,resulting in monotonous form,low robustness,and high costs.This paper focuses on the design of two-dimensional kinetic facades,proposing a hinged tessellation generation method based on the duality principle.First,the paper discusses the value and principles of applying dual graphs in HT,and then proposes a method of generating HT by adding hinged plates.Then,the operation process for different tessellation types is elaborated upon.Finally,a conceptual design is proposed to illustrate the potential of this method on kinetic facades.The method proposed in this paper is applicable to all uniform tessellations and Voronoi tessellations,capable of generating an infinite variety of planar expandable structures with small spatial thickness,simple structures,stable movements.Additionally,these structures can be driven to expand by a single driving point,enabling continuous adjustment in response to the requirement.It has significant application value in fields such as architectural and decorative design,structural design,mechanical design,industrial product and graphic design.
基金The National Natural Science Foundation of China (No60472018)
文摘A definition of a self-dual code on graph and a procedure based on factor graphs to judge a self-dual code were presented. Three contributions of this paper were described as follows. To begin with, transform T_ R→L were defined, which was the basis of self-dual codes defined on graphs and played a key role in the paper. The second were that a self-dual code could be defined on factor graph, which was much different from conventional algebraic method. The third was that a factor graph approach to judge a self-dual code was illustrated, which took advantage of duality properties of factor graphs and our proposed transform T_ R→L to offer a convenient and geometrically intuitive process to judge a self-dual code.
文摘陆地碳汇是碳循环的重要组成部分,在全球气候变化背景下其重要性日益凸显,相关研究受到了国内外学术界的广泛关注。采用文献计量方法,以1994—2024年间Web of Science核心合集SCI-E数据库以及CNKI数据库中所收录的共计8431篇相关文献为研究对象,运用CiteSpace软件绘制国内外文献共被引、作者共作以及关键词时间线等可视化图谱,分析了论文时间、学科、期刊以及来源国家的分布情况,给出了高影响机构、高产作者以及重要研究文献,并基于Burst检测探究了不同阶段关键词演化发展过程及未来趋势。结果表明:①近30 a来陆地碳汇发文量显著增长,2008年以后年均增幅12%,2019年以后年均增幅高达15%。②发文量较多的国家依次是中国、美国、德国、英国、加拿大等;高影响的研究机构主要有中国科学院、中国科学院大学、法国国家科学研究中心、美国农业部、巴黎-萨克雷大学等。③关键词演化过程主要分为3个阶段:1994—2008年侧重于碳循环基础理论研究,关键热词是碳循环、碳平衡和涡度相关等;2008—2019年研究热点从地球生态系统逐渐扩展到社会经济等方面,关键热词是净初级生产量、碳交换、生态补偿和低碳经济等;2019年至今紧密围绕全球碳减排目标与生态系统价值实现,关键热词是以碳中和、碳排放、温度敏感性、生态产品核算和碳交易;未来发展方向是碳汇监测核算、减排增汇提升方法、碳交易市场机制、深化国际合作等。研究成果可为厘清全球陆地碳汇发展脉络和研究热点、预测未来发展方向,以及促进我国双碳目标实现提供基础资料和政策建议。
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through the Large Group Research Project under grant number(R.G.P.2/181/44).
文摘Graph theory has a significant impact and is crucial in the structure of many real-life situations.To simulate uncertainty and ambiguity,many extensions of graph theoretical notions were created.Planar graphs play a vital role in modelling which has the property of non-crossing edges.Although crossing edges benefit,they have some drawbacks,which paved the way for the introduction of planar graphs.The overall purpose of the study is to contribute to the conceptual development of the Pythagorean Neutrosophic graph.The basic methodology of our research is the incorporation of the analogous concepts of planar graphs in the Pythagorean Neutrosophic graphs.The significant finding of our research is the introduction of Pythagorean Neutrosophic Planar graphs,a conceptual blending of Pythagorean Neutro-sophic and Planar graphs.The idea of Pythagorean Neutrosophic multigraphs and dual graphs are also introduced to deal with the ambiguous situations.This paper investigates the Pythagorean Neutrosophic planar values,which form the edges of the Pythagorean neutrosophic graphs.The concept of Pythagorean Neutrosophic dual graphs,isomorphism,co-weak and weak isomorphism have also been explored for Pythagorean Neutrosophic planar graphs.A decision-making algorithm was proposed with a numerical illustra-tion by using the Pythagorean Neutrosophic fuzzy graph.
文摘Fuzzy graph theory is used for solving real-world problems in different fields, in- cluding theoretical computer science, engineering, physics, combinatorics and medical sciences. In this paper, we present conepts of bipolar neutrosophic multigraphs, bipolar neutrosophic planar graphs, bipolar neutrosophic dual graphs, and study some of their related properties. We also describe applications of bipolar neutrosophic graphs in road network and electrical connections.
